There are two main components of risk assessment: tox-icological identification and exposure assessment. Biomarkers responding to oil exposure can be applied to determine the amount of oil taken up by organisms for ecological risk assessment. Researchers can also evaluate the possibility of adverse effects on organisms or the ecosystem so that regulatory agencies can respond more effectively to a given situation. A good biomarker needs to be specific to oil exposure, be reproducible, sensitive, applicable to both the laboratory and field, not prohibitively expensive, and easy to use. The most common biomarkers for oil exposure include the hepatic cyto-chrome P450 isozymes, fluorescent biliary aromatic compounds, heat shock (stress) proteins, DNA and chromosomal damage, histopathology, and multiple xenobiotic metabolic enzymes. Each method is unlikely to satisfactorily address all of the criteria. There are also other concerns, such as biomarker quantification, timing of analysis, and whether or not responses are reversible. However, the above general biomarkers can provide a fast screen of exposure and indicate the need for further analysis when initial results produce measurable differences.
Currently, there exists little information on biomar-kers of toxic responses for organisms exposed to oil. However, determining biological effects at sublethal concentrations will greatly assist risk assessment for chronic effects associated with development, reproduction, and survival. High-throughput analysis of genes, protein, or metabolites, followed by multivariate analysis, can potentially provide a powerful tool to accelerate the field of biomarker development. These high-throughput techniques can screen the changes of thousands of genes, proteins, or metabolites when organisms are exposed to oil at sublethal levels. The large mass of data will assess not only biomarker development, but mechanism studies. By studying the dynamic changes of biomarkers, researchers may better understand the biological impacts of oil in a more complete manner to predict the risk of different types of petroleum to different species.
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